Identifying data gaps through visualization

This tool helps researchers identify potential gaps in biodiversity data by visualizing richness and temporal distribution. 

Data resources used via GBIF : 10,000 species occurrences
Hooded Oriole (Icterus cucullatus)

Hooded Oriole (Icterus cucullatus) by bouriquer via Naturalista. Photo licensed under CC BY-NC 4.0.

Informatics is an integrated part of biodiversity science, and tools are becoming essential for researchers to download, process and visualise biodiversity data. The R environment is rapidly becoming the preferred platform for all kinds of data analysis, including biodiversity. This paper introduces a new R package, bdvis, that enables visualization of datasets to help identify temporal, spatial and taxonomic gaps. The package accepts downloads of occurrences from GBIF (via rgbif), VertNet (via rvertnet) and iNaturalist (via rinat) and can help data holders to improve quality of existing datasets, and data users to understand strengths and weaknesses in datasets. Through examples, the authors demonstrate how a dataset from GBIF can be downloaded, formatted and graphically visualized in just a few simple steps. The resulting graphs provide insights into possible gaps that should be considered by data users and potentially addressed by data holders.

Citations

Barve V and Otegui J (2016) bdvis: visualizing biodiversity data in R. Bioinformatics. Oxford University Press (OUP) 32(19): 3049–3050. Available at doi:10.1093/bioinformatics/btw333.

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